Bank Data Analysis Report

Dataset statistics

Number of variables	15
Number of observations	1000
Missing cells	634
Missing cells (%)	4.2%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	117.3 KiB
Average record size in memory	120.1 B

Variable types

Numeric	8
Categorical	7

Alerts

`join_date` has constant value "54:25.3"	Constant
`age` has 53 (5.3%) missing values	Missing
`gender` has 48 (4.8%) missing values	Missing
`region` has 52 (5.2%) missing values	Missing
`education_level` has 51 (5.1%) missing values	Missing
`employment_type` has 54 (5.4%) missing values	Missing
`annual_income` has 50 (5.0%) missing values	Missing
`loan_amount` has 44 (4.4%) missing values	Missing
`loan_purpose` has 37 (3.7%) missing values	Missing
`credit_score` has 45 (4.5%) missing values	Missing
`repayment_history` has 46 (4.6%) missing values	Missing
`transaction_count` has 49 (4.9%) missing values	Missing
`spending_ratio` has 49 (4.9%) missing values	Missing
`join_date` has 56 (5.6%) missing values	Missing
`customer_id` is uniformly distributed	Uniform
`customer_id` has unique values	Unique
`repayment_history` has 71 (7.1%) zeros	Zeros

Reproduction

Analysis started	2026-02-17 10:46:40.917489
Analysis finished	2026-02-17 10:46:59.810053
Duration	18.89 seconds
Software version	ydata-profiling vv4.18.1
Download configuration	config.json

customer_id
Real number (ℝ)

Uniform Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1500.5

Minimum	1001
Maximum	2000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	1001
5-th percentile	1050.95
Q1	1250.75
median	1500.5
Q3	1750.25
95-th percentile	1950.05
Maximum	2000
Range	999
Interquartile range (IQR)	499.5

Descriptive statistics

Standard deviation	288.81944
Coefficient of variation (CV)	0.19248213
Kurtosis	-1.2
Mean	1500.5
Median Absolute Deviation (MAD)	250
Skewness	0
Sum	1500500
Variance	83416.667
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1001	1	0.1%
1002	1	0.1%
1003	1	0.1%
1004	1	0.1%
1005	1	0.1%
1006	1	0.1%
1007	1	0.1%
1008	1	0.1%
1009	1	0.1%
1010	1	0.1%
Other values (990)	990	99.0%

Value	Count	Frequency (%)
1001	1	0.1%
1002	1	0.1%
1003	1	0.1%
1004	1	0.1%
1005	1	0.1%
1006	1	0.1%
1007	1	0.1%
1008	1	0.1%
1009	1	0.1%
1010	1	0.1%

Value	Count	Frequency (%)
2000	1	0.1%
1999	1	0.1%
1998	1	0.1%
1997	1	0.1%
1996	1	0.1%
1995	1	0.1%
1994	1	0.1%
1993	1	0.1%
1992	1	0.1%
1991	1	0.1%

age
Real number (ℝ)

Missing

Distinct	52
Distinct (%)	5.5%
Missing	53
Missing (%)	5.3%
Infinite	0
Infinite (%)	0.0%
Mean	43.726505

Minimum	18
Maximum	69
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	18
5-th percentile	20
Q1	31
median	44
Q3	56
95-th percentile	67
Maximum	69
Range	51
Interquartile range (IQR)	25

Descriptive statistics

Standard deviation	14.997539
Coefficient of variation (CV)	0.34298509
Kurtosis	-1.1368642
Mean	43.726505
Median Absolute Deviation (MAD)	12
Skewness	-0.027393374
Sum	41409
Variance	224.92618
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
43	28	2.8%
52	27	2.7%
50	26	2.6%
45	26	2.6%
66	25	2.5%
54	22	2.2%
22	22	2.2%
68	22	2.2%
40	22	2.2%
19	21	2.1%
Other values (42)	706	70.6%
(Missing)	53	5.3%

Value	Count	Frequency (%)
18	21	2.1%
19	21	2.1%
20	19	1.9%
21	15	1.5%
22	22	2.2%
23	15	1.5%
24	14	1.4%
25	20	2.0%
26	17	1.7%
27	14	1.4%

Value	Count	Frequency (%)
69	21	2.1%
68	22	2.2%
67	15	1.5%
66	25	2.5%
65	19	1.9%
64	20	2.0%
63	10	1.0%
62	21	2.1%
61	17	1.7%
60	11	1.1%

gender
Categorical

Missing

Distinct	3
Distinct (%)	0.3%
Missing	48
Missing (%)	4.8%
Memory size	7.9 KiB

Male	325
Female	317
Other	310

Length

Max length	6
Median length	5
Mean length	4.9915966
Min length	4

Characters and Unicode

Total characters	4752
Distinct characters	10
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Other
2nd row	Other
3rd row	Other
4th row	Male
5th row	Other

Common Values

Value	Count	Frequency (%)
Male	325	32.5%
Female	317	31.7%
Other	310	31.0%
(Missing)	48	4.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
male	325	34.1%
female	317	33.3%
other	310	32.6%

Most occurring characters

Value	Count	Frequency (%)
e	1269	26.7%
a	642	13.5%
l	642	13.5%
M	325	6.8%
F	317	6.7%
m	317	6.7%
O	310	6.5%
t	310	6.5%
h	310	6.5%
r	310	6.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4752	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1269	26.7%
a	642	13.5%
l	642	13.5%
M	325	6.8%
F	317	6.7%
m	317	6.7%
O	310	6.5%
t	310	6.5%
h	310	6.5%
r	310	6.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4752	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1269	26.7%
a	642	13.5%
l	642	13.5%
M	325	6.8%
F	317	6.7%
m	317	6.7%
O	310	6.5%
t	310	6.5%
h	310	6.5%
r	310	6.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4752	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1269	26.7%
a	642	13.5%
l	642	13.5%
M	325	6.8%
F	317	6.7%
m	317	6.7%
O	310	6.5%
t	310	6.5%
h	310	6.5%
r	310	6.5%

region
Categorical

Missing

Distinct	4
Distinct (%)	0.4%
Missing	52
Missing (%)	5.2%
Memory size	7.9 KiB

South	261
North	241
West	234
East	212

Length

Max length	5
Median length	5
Mean length	4.5295359
Min length	4

Characters and Unicode

Total characters	4294
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	North
2nd row	West
3rd row	South
4th row	South
5th row	East

Common Values

Value	Count	Frequency (%)
South	261	26.1%
North	241	24.1%
West	234	23.4%
East	212	21.2%
(Missing)	52	5.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
south	261	27.5%
north	241	25.4%
west	234	24.7%
east	212	22.4%

Most occurring characters

Value	Count	Frequency (%)
t	948	22.1%
o	502	11.7%
h	502	11.7%
s	446	10.4%
u	261	6.1%
S	261	6.1%
r	241	5.6%
N	241	5.6%
W	234	5.4%
e	234	5.4%
Other values (2)	424	9.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4294	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
t	948	22.1%
o	502	11.7%
h	502	11.7%
s	446	10.4%
u	261	6.1%
S	261	6.1%
r	241	5.6%
N	241	5.6%
W	234	5.4%
e	234	5.4%
Other values (2)	424	9.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4294	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
t	948	22.1%
o	502	11.7%
h	502	11.7%
s	446	10.4%
u	261	6.1%
S	261	6.1%
r	241	5.6%
N	241	5.6%
W	234	5.4%
e	234	5.4%
Other values (2)	424	9.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4294	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
t	948	22.1%
o	502	11.7%
h	502	11.7%
s	446	10.4%
u	261	6.1%
S	261	6.1%
r	241	5.6%
N	241	5.6%
W	234	5.4%
e	234	5.4%
Other values (2)	424	9.9%

education_level
Categorical

Missing

Distinct	4
Distinct (%)	0.4%
Missing	51
Missing (%)	5.1%
Memory size	7.9 KiB

Post-Graduate	266
Secondary	233
Graduate	226
Primary	224

Length

Max length	13
Median length	9
Mean length	9.4109589
Min length	7

Characters and Unicode

Total characters	8931
Distinct characters	17
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Graduate
2nd row	Post-Graduate
3rd row	Primary
4th row	Graduate
5th row	Post-Graduate

Common Values

Value	Count	Frequency (%)
Post-Graduate	266	26.6%
Secondary	233	23.3%
Graduate	226	22.6%
Primary	224	22.4%
(Missing)	51	5.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
post-graduate	266	28.0%
secondary	233	24.6%
graduate	226	23.8%
primary	224	23.6%

Most occurring characters

Value	Count	Frequency (%)
a	1441	16.1%
r	1173	13.1%
t	758	8.5%
e	725	8.1%
d	725	8.1%
o	499	5.6%
u	492	5.5%
G	492	5.5%
P	490	5.5%
y	457	5.1%
Other values (7)	1679	18.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	8931	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	1441	16.1%
r	1173	13.1%
t	758	8.5%
e	725	8.1%
d	725	8.1%
o	499	5.6%
u	492	5.5%
G	492	5.5%
P	490	5.5%
y	457	5.1%
Other values (7)	1679	18.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	8931	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	1441	16.1%
r	1173	13.1%
t	758	8.5%
e	725	8.1%
d	725	8.1%
o	499	5.6%
u	492	5.5%
G	492	5.5%
P	490	5.5%
y	457	5.1%
Other values (7)	1679	18.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	8931	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	1441	16.1%
r	1173	13.1%
t	758	8.5%
e	725	8.1%
d	725	8.1%
o	499	5.6%
u	492	5.5%
G	492	5.5%
P	490	5.5%
y	457	5.1%
Other values (7)	1679	18.8%

employment_type
Categorical

Missing

Distinct	3
Distinct (%)	0.3%
Missing	54
Missing (%)	5.4%
Memory size	7.9 KiB

Salaried	333
Unemployed	322
Self-Employed	291

Length

Max length	13
Median length	10
Mean length	10.218816
Min length	8

Characters and Unicode

Total characters	9667
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Unemployed
2nd row	Self-Employed
3rd row	Unemployed
4th row	Salaried
5th row	Salaried

Common Values

Value	Count	Frequency (%)
Salaried	333	33.3%
Unemployed	322	32.2%
Self-Employed	291	29.1%
(Missing)	54	5.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
salaried	333	35.2%
unemployed	322	34.0%
self-employed	291	30.8%

Most occurring characters

Value	Count	Frequency (%)
e	1559	16.1%
l	1237	12.8%
d	946	9.8%
a	666	6.9%
S	624	6.5%
o	613	6.3%
p	613	6.3%
m	613	6.3%
y	613	6.3%
r	333	3.4%
Other values (6)	1850	19.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	9667	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1559	16.1%
l	1237	12.8%
d	946	9.8%
a	666	6.9%
S	624	6.5%
o	613	6.3%
p	613	6.3%
m	613	6.3%
y	613	6.3%
r	333	3.4%
Other values (6)	1850	19.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	9667	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1559	16.1%
l	1237	12.8%
d	946	9.8%
a	666	6.9%
S	624	6.5%
o	613	6.3%
p	613	6.3%
m	613	6.3%
y	613	6.3%
r	333	3.4%
Other values (6)	1850	19.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	9667	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1559	16.1%
l	1237	12.8%
d	946	9.8%
a	666	6.9%
S	624	6.5%
o	613	6.3%
p	613	6.3%
m	613	6.3%
y	613	6.3%
r	333	3.4%
Other values (6)	1850	19.1%

annual_income
Real number (ℝ)

Missing

Distinct	950
Distinct (%)	100.0%
Missing	50
Missing (%)	5.0%
Infinite	0
Infinite (%)	0.0%
Mean	598976.8

Minimum	-64951.14
Maximum	1212389.4
Zeros	0
Zeros (%)	0.0%
Negative	1
Negative (%)	0.1%
Memory size	7.9 KiB

Quantile statistics

Minimum	-64951.14
5-th percentile	271672.07
Q1	463669.3
median	598894.3
Q3	737418.18
95-th percentile	918892.45
Maximum	1212389.4
Range	1277340.5
Interquartile range (IQR)	273748.87

Descriptive statistics

Standard deviation	195456.74
Coefficient of variation (CV)	0.32631772
Kurtosis	-0.25766435
Mean	598976.8
Median Absolute Deviation (MAD)	136607.72
Skewness	-0.034094904
Sum	5.6902796 × 10⁸
Variance	3.8203338 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
726722.31	1	0.1%
617593.76	1	0.1%
121745.11	1	0.1%
585024.81	1	0.1%
690836.63	1	0.1%
493053.35	1	0.1%
457501.16	1	0.1%
888884.08	1	0.1%
587942.2	1	0.1%
690959.03	1	0.1%
Other values (940)	940	94.0%
(Missing)	50	5.0%

Value	Count	Frequency (%)
-64951.14	1	0.1%
63042.39	1	0.1%
67133.54	1	0.1%
121745.11	1	0.1%
125949.5	1	0.1%
133869.05	1	0.1%
135608.72	1	0.1%
150371.42	1	0.1%
152734.19	1	0.1%
158716.23	1	0.1%

Value	Count	Frequency (%)
1212389.39	1	0.1%
1153195.92	1	0.1%
1136934.85	1	0.1%
1110937.27	1	0.1%
1082009.73	1	0.1%
1070041.16	1	0.1%
1043840.25	1	0.1%
1022027.12	1	0.1%
1016153.18	1	0.1%
1015127.51	1	0.1%

loan_amount
Real number (ℝ)

Missing

Distinct	956
Distinct (%)	100.0%
Missing	44
Missing (%)	4.4%
Infinite	0
Infinite (%)	0.0%
Mean	298443.54

Minimum	9553.56
Maximum	564503.68
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	9553.56
5-th percentile	137258.1
Q1	231770.91
median	294768.7
Q3	365947.58
95-th percentile	463612.47
Maximum	564503.68
Range	554950.12
Interquartile range (IQR)	134176.67

Descriptive statistics

Standard deviation	99556.028
Coefficient of variation (CV)	0.33358412
Kurtosis	-0.14050116
Mean	298443.54
Median Absolute Deviation (MAD)	66926.095
Skewness	0.055598952
Sum	2.8531203 × 10⁸
Variance	9.9114026 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
516400.74	1	0.1%
359873.9	1	0.1%
207976.15	1	0.1%
97458.19	1	0.1%
380892.47	1	0.1%
262581.97	1	0.1%
284443.43	1	0.1%
376619.6	1	0.1%
401041.38	1	0.1%
422371.03	1	0.1%
Other values (946)	946	94.6%
(Missing)	44	4.4%

Value	Count	Frequency (%)
9553.56	1	0.1%
10010.62	1	0.1%
27772.23	1	0.1%
28675.74	1	0.1%
35910.23	1	0.1%
37293.46	1	0.1%
37932.9	1	0.1%
41158.34	1	0.1%
50150.64	1	0.1%
62356.71	1	0.1%

Value	Count	Frequency (%)
564503.68	1	0.1%
563769.49	1	0.1%
556990.7	1	0.1%
551153.96	1	0.1%
550164.5	1	0.1%
548497	1	0.1%
544458.28	1	0.1%
544150.43	1	0.1%
541421.73	1	0.1%
539076.62	1	0.1%

loan_purpose
Categorical

Missing

Distinct	5
Distinct (%)	0.5%
Missing	37
Missing (%)	3.7%
Memory size	7.9 KiB

Car	226
Other	198
Education	190
Home	175
Business	174

Length

Max length	9
Median length	5
Mean length	5.6801661
Min length	3

Characters and Unicode

Total characters	5470
Distinct characters	18
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Home
2nd row	Car
3rd row	Home
4th row	Other
5th row	Business

Common Values

Value	Count	Frequency (%)
Car	226	22.6%
Other	198	19.8%
Education	190	19.0%
Home	175	17.5%
Business	174	17.4%
(Missing)	37	3.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
car	226	23.5%
other	198	20.6%
education	190	19.7%
home	175	18.2%
business	174	18.1%

Most occurring characters

Value	Count	Frequency (%)
e	547	10.0%
s	522	9.5%
r	424	7.8%
a	416	7.6%
t	388	7.1%
o	365	6.7%
i	364	6.7%
n	364	6.7%
u	364	6.7%
C	226	4.1%
Other values (8)	1490	27.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5470	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	547	10.0%
s	522	9.5%
r	424	7.8%
a	416	7.6%
t	388	7.1%
o	365	6.7%
i	364	6.7%
n	364	6.7%
u	364	6.7%
C	226	4.1%
Other values (8)	1490	27.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5470	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	547	10.0%
s	522	9.5%
r	424	7.8%
a	416	7.6%
t	388	7.1%
o	365	6.7%
i	364	6.7%
n	364	6.7%
u	364	6.7%
C	226	4.1%
Other values (8)	1490	27.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5470	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	547	10.0%
s	522	9.5%
r	424	7.8%
a	416	7.6%
t	388	7.1%
o	365	6.7%
i	364	6.7%
n	364	6.7%
u	364	6.7%
C	226	4.1%
Other values (8)	1490	27.2%

credit_score
Real number (ℝ)

Missing

Distinct	261
Distinct (%)	27.3%
Missing	45
Missing (%)	4.5%
Infinite	0
Infinite (%)	0.0%
Mean	646.82199

Minimum	476
Maximum	837
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	476
5-th percentile	545
Q1	608.5
median	646
Q3	687
95-th percentile	750
Maximum	837
Range	361
Interquartile range (IQR)	78.5

Descriptive statistics

Standard deviation	60.788751
Coefficient of variation (CV)	0.09398065
Kurtosis	0.1084169
Mean	646.82199
Median Absolute Deviation (MAD)	39
Skewness	0.11856696
Sum	617715
Variance	3695.2723
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
655	12	1.2%
652	11	1.1%
651	11	1.1%
639	11	1.1%
649	11	1.1%
630	10	1.0%
619	9	0.9%
656	9	0.9%
599	9	0.9%
638	9	0.9%
Other values (251)	853	85.3%
(Missing)	45	4.5%

Value	Count	Frequency (%)
476	1	0.1%
480	1	0.1%
486	1	0.1%
497	1	0.1%
498	1	0.1%
499	1	0.1%
500	1	0.1%
504	1	0.1%
506	1	0.1%
507	1	0.1%

Value	Count	Frequency (%)
837	1	0.1%
836	1	0.1%
826	2	0.2%
825	1	0.1%
819	1	0.1%
812	1	0.1%
805	1	0.1%
804	1	0.1%
802	1	0.1%
800	2	0.2%

repayment_history
Real number (ℝ)

Missing Zeros

Distinct	13
Distinct (%)	1.4%
Missing	46
Missing (%)	4.6%
Infinite	0
Infinite (%)	0.0%
Mean	6.0880503

Minimum	0
Maximum	12
Zeros	71
Zeros (%)	7.1%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3
median	6
Q3	9
95-th percentile	12
Maximum	12
Range	12
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	3.7927146
Coefficient of variation (CV)	0.62297688
Kurtosis	-1.2234114
Mean	6.0880503
Median Absolute Deviation (MAD)	3
Skewness	-0.015684887
Sum	5808
Variance	14.384684
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
12	93	9.3%
8	86	8.6%
6	82	8.2%
2	81	8.1%
9	75	7.5%
1	74	7.4%
5	73	7.3%
3	72	7.2%
0	71	7.1%
10	67	6.7%
Other values (3)	180	18.0%

Value	Count	Frequency (%)
0	71	7.1%
1	74	7.4%
2	81	8.1%
3	72	7.2%
4	54	5.4%
5	73	7.3%
6	82	8.2%
7	63	6.3%
8	86	8.6%
9	75	7.5%

Value	Count	Frequency (%)
12	93	9.3%
11	63	6.3%
10	67	6.7%
9	75	7.5%
8	86	8.6%
7	63	6.3%
6	82	8.2%
5	73	7.3%
4	54	5.4%
3	72	7.2%

transaction_count
Real number (ℝ)

Missing

Distinct	199
Distinct (%)	20.9%
Missing	49
Missing (%)	4.9%
Infinite	0
Infinite (%)	0.0%
Mean	98.44795

Minimum	1
Maximum	199
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	1
5-th percentile	11
Q1	50
median	96
Q3	147
95-th percentile	189
Maximum	199
Range	198
Interquartile range (IQR)	97

Descriptive statistics

Standard deviation	57.346749
Coefficient of variation (CV)	0.58250832
Kurtosis	-1.2035856
Mean	98.44795
Median Absolute Deviation (MAD)	48
Skewness	0.047010588
Sum	93624
Variance	3288.6497
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
134	11	1.1%
192	11	1.1%
187	10	1.0%
48	10	1.0%
181	9	0.9%
15	9	0.9%
86	8	0.8%
74	8	0.8%
164	8	0.8%
26	8	0.8%
Other values (189)	859	85.9%
(Missing)	49	4.9%

Value	Count	Frequency (%)
1	6	0.6%
2	4	0.4%
3	4	0.4%
4	6	0.6%
5	3	0.3%
6	2	0.2%
7	3	0.3%
8	7	0.7%
9	5	0.5%
10	7	0.7%

Value	Count	Frequency (%)
199	4	0.4%
198	5	0.5%
197	6	0.6%
196	2	0.2%
195	4	0.4%
194	1	0.1%
193	4	0.4%
192	11	1.1%
191	4	0.4%
190	5	0.5%

spending_ratio
Real number (ℝ)

Missing

Distinct	891
Distinct (%)	93.7%
Missing	49
Missing (%)	4.9%
Infinite	0
Infinite (%)	0.0%
Mean	44.554311

Minimum	10
Maximum	79.9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	10
5-th percentile	13.575
Q1	28.55
median	44.55
Q3	60.84
95-th percentile	75.95
Maximum	79.9
Range	69.9
Interquartile range (IQR)	32.29

Descriptive statistics

Standard deviation	19.5181
Coefficient of variation (CV)	0.43807433
Kurtosis	-1.1208868
Mean	44.554311
Median Absolute Deviation (MAD)	16.17
Skewness	0.024878433
Sum	42371.15
Variance	380.95622
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
15.87	3	0.3%
58.67	3	0.3%
54.62	2	0.2%
38.5	2	0.2%
19.38	2	0.2%
43.36	2	0.2%
19.68	2	0.2%
44.73	2	0.2%
36.32	2	0.2%
60.43	2	0.2%
Other values (881)	929	92.9%
(Missing)	49	4.9%

Value	Count	Frequency (%)
10	1	0.1%
10.06	1	0.1%
10.18	1	0.1%
10.31	1	0.1%
10.37	1	0.1%
10.39	1	0.1%
10.4	1	0.1%
10.57	1	0.1%
10.65	2	0.2%
10.68	1	0.1%

Value	Count	Frequency (%)
79.9	1	0.1%
79.89	1	0.1%
79.79	1	0.1%
79.5	1	0.1%
79.44	1	0.1%
79.42	1	0.1%
79.22	1	0.1%
79.05	1	0.1%
79.02	2	0.2%
78.79	1	0.1%

join_date
Categorical

Constant Missing

Distinct	1
Distinct (%)	0.1%
Missing	56
Missing (%)	5.6%
Memory size	7.9 KiB

54:25.3	944

Length

Max length	7
Median length	7
Mean length	7
Min length	7

Characters and Unicode

Total characters	6608
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	54:25.3
2nd row	54:25.3
3rd row	54:25.3
4th row	54:25.3
5th row	54:25.3

Common Values

Value	Count	Frequency (%)
54:25.3	944	94.4%
(Missing)	56	5.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
54:25.3	944	100.0%

Most occurring characters

Value	Count	Frequency (%)
5	1888	28.6%
4	944	14.3%
:	944	14.3%
2	944	14.3%
.	944	14.3%
3	944	14.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	6608	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
5	1888	28.6%
4	944	14.3%
:	944	14.3%
2	944	14.3%
.	944	14.3%
3	944	14.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	6608	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
5	1888	28.6%
4	944	14.3%
:	944	14.3%
2	944	14.3%
.	944	14.3%
3	944	14.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	6608	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
5	1888	28.6%
4	944	14.3%
:	944	14.3%
2	944	14.3%
.	944	14.3%
3	944	14.3%

default_flag
Categorical

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

0	843
1	157

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	843	84.3%
1	157	15.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	843	84.3%
1	157	15.7%

Most occurring characters

Value	Count	Frequency (%)
0	843	84.3%
1	157	15.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	843	84.3%
1	157	15.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	843	84.3%
1	157	15.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	843	84.3%
1	157	15.7%

	age	annual_income	credit_score	customer_id	default_flag	education_level	employment_type	gender	loan_amount	loan_purpose	region	repayment_history	spending_ratio	transaction_count
age	1.000	-0.022	0.022	-0.013	0.028	0.000	0.072	0.000	-0.082	0.000	0.000	0.055	0.007	0.036
annual_income	-0.022	1.000	-0.014	-0.016	0.076	0.000	0.000	0.000	-0.009	0.025	0.046	-0.010	-0.023	0.082
credit_score	0.022	-0.014	1.000	-0.061	0.051	0.000	0.000	0.000	0.058	0.000	0.000	0.028	0.026	0.009
customer_id	-0.013	-0.016	-0.061	1.000	0.051	0.000	0.046	0.000	-0.023	0.000	0.000	0.022	-0.035	-0.047
default_flag	0.028	0.076	0.051	0.051	1.000	0.000	0.000	0.000	0.000	0.000	0.037	0.000	0.000	0.111
education_level	0.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.015	0.035	0.000	0.083	0.000	0.011
employment_type	0.072	0.000	0.000	0.046	0.000	0.000	1.000	0.000	0.000	0.056	0.000	0.000	0.000	0.000
gender	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000	0.048	0.000	0.044	0.000	0.000	0.096
loan_amount	-0.082	-0.009	0.058	-0.023	0.000	0.015	0.000	0.048	1.000	0.000	0.032	0.029	-0.011	0.021
loan_purpose	0.000	0.025	0.000	0.000	0.000	0.035	0.056	0.000	0.000	1.000	0.051	0.000	0.000	0.000
region	0.000	0.046	0.000	0.000	0.037	0.000	0.000	0.044	0.032	0.051	1.000	0.051	0.036	0.012
repayment_history	0.055	-0.010	0.028	0.022	0.000	0.083	0.000	0.000	0.029	0.000	0.051	1.000	-0.022	-0.019
spending_ratio	0.007	-0.023	0.026	-0.035	0.000	0.000	0.000	0.000	-0.011	0.000	0.036	-0.022	1.000	-0.046
transaction_count	0.036	0.082	0.009	-0.047	0.111	0.011	0.000	0.096	0.021	0.000	0.012	-0.019	-0.046	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

	customer_id	age	gender	region	education_level	employment_type	annual_income	loan_amount	loan_purpose	credit_score	repayment_history	transaction_count	spending_ratio	join_date	default_flag
0	1001	56.0	Other	North	Graduate	Unemployed	763214.57	214669.67	Home	742.0	9.0	121.0	78.16	54:25.3	0
1	1002	69.0	Other	West	Post-Graduate	Self-Employed	585157.80	308528.42	Car	717.0	8.0	61.0	26.14	54:25.3	1
2	1003	46.0	Other	South	Primary	Unemployed	817492.83	418049.09	Home	622.0	2.0	100.0	64.10	54:25.3	0
3	1004	32.0	Male	South	Graduate	Salaried	784832.36	527840.20	Other	683.0	11.0	51.0	33.73	54:25.3	0
4	1005	60.0	Other	East	NaN	Salaried	515473.29	365736.50	Business	NaN	2.0	98.0	20.02	54:25.3	0
5	1006	25.0	Male	South	Post-Graduate	Salaried	735319.60	172959.13	Car	724.0	9.0	137.0	70.05	54:25.3	0
6	1007	38.0	Female	South	Post-Graduate	Salaried	492808.17	497086.43	Business	709.0	8.0	2.0	31.62	54:25.3	0
7	1008	NaN	Other	East	Primary	Self-Employed	NaN	298053.13	Business	566.0	9.0	5.0	56.12	54:25.3	1
8	1009	36.0	Male	South	Graduate	Salaried	340176.67	216229.06	Education	685.0	2.0	190.0	NaN	54:25.3	0
9	1010	40.0	Male	South	Primary	Self-Employed	355557.64	192060.75	Education	638.0	7.0	197.0	43.02	54:25.3	0

	customer_id	age	gender	region	education_level	employment_type	annual_income	loan_amount	loan_purpose	credit_score	repayment_history	transaction_count	spending_ratio	join_date
990	1991	24.0	Female	East	Graduate	Salaried	749006.11	186282.12	Home	689.0	4.0	145.0	54.38	NaN
991	1992	20.0	Female	South	Post-Graduate	Unemployed	887889.14	210717.04	Business	655.0	4.0	NaN	63.26	54:25.3
992	1993	64.0	Male	West	Graduate	Salaried	508090.21	453293.34	Business	545.0	10.0	59.0	79.02	54:25.3
993	1994	40.0	Female	NaN	Post-Graduate	NaN	252377.67	303270.78	Home	598.0	6.0	54.0	22.63	54:25.3
994	1995	NaN	Male	South	Secondary	Salaried	809050.20	310168.54	Education	690.0	NaN	86.0	63.62	54:25.3
995	1996	60.0	Male	West	Primary	Salaried	669953.90	310565.38	Education	660.0	3.0	12.0	33.72	54:25.3
996	1997	64.0	Male	North	Primary	Unemployed	540790.78	439462.54	Car	721.0	8.0	192.0	22.29	54:25.3
997	1998	62.0	Male	East	Primary	Self-Employed	551969.44	195478.56	Business	674.0	12.0	6.0	39.50	54:25.3
998	1999	35.0	Female	North	Primary	Unemployed	1110937.27	260360.45	Education	592.0	10.0	53.0	65.57	54:25.3
999	2000	55.0	Male	West	Primary	Unemployed	471561.07	283103.48	Education	602.0	9.0	144.0	42.54	54:25.3

Overview

Variables

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)